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Well written whitepaper. It could however be improved by adding on several real-life operational realities to make it more meaningful & drive future ATM planning & implementation programs. For e.g. there could be a strong focus that Data Science brings to improve Airspace Planning- whether it is designing new airways, or more dynamically with an organized track system such as in the N.Atlantic and other similar oceanic areas or even bench marking the success of PBN procedures in the TMAs to manage noiseCO2 and improve on efficient procedures. . There is a major element that aircraft systems could play in providing connectivity to ground systems through COM systems such as plain old ACARS, NAV systems that in turn are linked through avionics such as the Mode S extended squitter to downlink aircraft parameters (DAPs) or even cooperative surveillance systems such as ADS-B out. SOmetimes, it could be a simple matter of contracting airlines to share their OOOI data and leveraging a very rich dataset that Flow Management systems such as CFMU (NOP) – IFPS already have. Also missing the element of blending FIled FPL data with flown data to deliver a reality check on meeting Airspace user ‘business trajectories’ on the one hand and capacity demand/supply for ATC sectors on the other hand. Blend in the element of tactical Flow & Capacity management and CDM, it becomes even more meaningful. Not to forget the aspects of Airports, Enroute and MET costs into the ‘profit & loss’ statement of each flight to break down the direct time-dependent airline block costs… and one can go on……..!!!